Introducing new content items in a community-based recommendation system

ABSTRACT

The invention relates to a method of operating with content items, generating of a user preference profile, and introducing new content items in a community-based recommendation system. A virtual user terminal ( 115 ) determines a new user preference profile when detecting the availability of a new content item. The virtual user terminal ( 115 ) comprises an initialization processor ( 123 ) which sets a preference value in the user preference profile for the new content item. The virtual user terminal ( 115 ) further comprises a relation processor ( 125 ) which determines related content items, and a profile processor ( 127 ), which sets preference values in the user preference profile associated with the at least one related content item. Hence, an association is formed between the first content item and the related content items, thereby linking the new content item to existing content items, and thus increasing the probability that the new content item is recommended.

The invention relates to a method and apparatus for operating withcontent items in a community-based recommendation system.

In recent years, the accessibility to and provision of information andcontent such as TV programs, film, music and books, etc. have increasedexplosively. Especially, the advent of the Internet as an increasinglyavailable source of information has resulted in the main problem thatfaces most users, namely not whether appropriate information or contentis available but how this can be found. Specifically, it has becomeincreasingly important that the services and content provided to a userare targeted to this user and thus meet his specific user profile andreflect his personal preferences.

One method of customizing e.g. the information and content provision toa specific user is a recommendation-based approach, wherein specificcontent or information is determined to be suited for a user andtherefore recommended to him. One recommendation approach is acommunity-based recommendation approach, wherein feedback andpreferences received from a suitable community are used to determinerecommendations for a user in that community. Thus, for example, certainbehaviors or actions are observed and categorized for a community, andif another user exhibits a similar behavior, the information or contentaccessed by users in that category may be recommended.

An example of a community-based recommendation system is known fromseveral e-commerce Internet sites, wherein the purchasing behavior ofusers is monitored. A user having a purchasing behavior similar to astored behavior is recommended purchases similar or identical topurchases made by other users in that group. A well-known example iswhen a purchaser of a book is recommended a number of other books thathave been purchased by other users also purchasing the current book.

Typically, community-based recommendation systems operate by comparinguser profiles of different users and recommending users content thatother users having similar profiles have preferred. However, typically,users will therefore only or predominantly be recommended content thathas already been evaluated by other users. Typically, forcommunity-based recommendation systems, the recommendations made tend tobe of content with the highest prevalence in user profiles. Therefore,the more user profiles comprise a given content, the more likely it isto be recommended to another user. The more a content item isrecommended, the more likely it is to be included in a user profile, andas the probability of a content item being recommended increases withincreased dissemination, a community-based recommendation systemtypically has a tendency towards providing undesirably narrowrecommendations of mainly the most popular content items. Therecommendations may further become increasingly narrow over time andthus do not provide a desired flexibility and diversity in therecommendations. Specifically, it tends to be difficult for a newcontent item to be introduced to a community-based recommendation systemwithout an undesirable latency.

Also, as typical community-based recommendation systems tend to be basedon a number of user profiles, it may be difficult to impact therecommendations performed by the community-based recommendation system.Furthermore, in most community-based recommendation systems, no otherway of affecting the recommendations than through user profiles ispossible. For example, in a centrally operated community-basedrecommendation system, wherein the recommendations are made by a centralrecommender, only the operator of the recommender can affect therecommendations, except through user profiles.

Hence, an improved community-based recommendation would be advantageousand in particular community-based recommendations allowing an increasedflexibility, diversity and/or means for influencing the recommendationswould be advantageous.

Accordingly, the invention seeks to provide means allowing improvedcommunity-based recommendations. Preferably, the invention tends toimprove the performance of a community-based recommendation systemand/or to allow an increased flexibility, diversity and/or means forinfluencing the recommendations.

According to a first aspect of the invention, a method of operating withcontent items in a community-based recommendation system comprises thesteps of: initializing a first element of a user preference profile witha first preference value, the first element being associated with afirst content item; determining at least one related content itemrelated to the first content item; setting a second preference value ofan element of the user preference profile associated with the at leastone related content item.

The invention enables recommendations to be made in response to thepreferences determined in the user preference profile, and specificallyin response to the association made by the user preference profilebetween the first content item and the at least one related contentitem. Specifically, the first and second preference values may be set tocause a recommender to associate the first content item with the atleast one related content item. Hence, the user preference profile maypreferably be included in a community-based recommendation system,thereby resulting in associations being formed between the first contentitem and the at least one related content item. This may specificallycause the first content item to be recommended to users having highpreference values for the at least one related content item. Forexample, a new first content item may thus be introduced to acommunity-based recommendation system by a user preference profilewherein both the user preference for a new content item as well aspreference values for existing content items are set to cause anassociation between these. Hence, the user preference profile mayintroduce the first content item to the community and may specificallytarget a specific group of the community by an appropriate setting ofthe preference values for related content items. This allows a targetedand directed introduction of new content items.

The user preference profile may specifically be compatible with a givencommunity-based recommendation system. The user preference profile maythus allow the recommendations of a community-based recommendationsystem to be influenced. The method provides a very flexiblerecommendation system. It further provides an efficient and easy way toimplement means for increasing the diversity and variation ofrecommendations. Specifically, it allows new content to be introduced toa community-based recommendation system, and this to be recommended.Specifically, the user preference profile may allow an association to bemade between a new first content item and content item already includedin the recommendation system. The user preference profile mayspecifically be generated as an update or modification to an existinguser preference profile.

According to a feature of the invention, the second preference value issimilar to the first preference value. Hence, the preference value ofthe related content item may be similar to that of the first contentitem. Specifically, an association of the first content item with the atleast one related content item is achieved by setting the preferencevalue for these content items to be similar, for example by setting themto be equivalent or substantially identical. This provides a suitablemeans for association, which is compatible with most community-basedrecommendation systems. Hence, related contents are preferably set tohave similar preference values.

According to another feature of the invention, the first preferencevalue is a high preference value. This allows a high preference value tobe set for the first content item, thereby causing a high probability ofthe first content item being recommended to other users of thecommunity-based recommendation system. Specifically, by setting thesecond preference value high in the user preference profile, a greatprobability of recommendation of the first content item to users havinga high preference for the at least one related content item is achieved.

According to another feature of the invention, an equivalence of thefirst preference value and the second preference value is determined inresponse to a degree of similarity between the first content item andthe at least one related content item. Specifically, the equivalencebetween the first and second preference values may be increased forincreasing similarity between the first content item and the at leastone related content item. This allows a further refinement ininfluencing recommendations.

According to another feature of the invention, the method furthercomprises the steps of determining if the first content item is a newcontent item, wherein the steps of initializing, determining and settingare only performed if the first content item is new. The method mayspecifically consider a plurality of content items and for each of thesedetermine if the content item is a new content item. The generation of auser preference profile may only be performed for new content items. Forexample, the method may be comprised in a functional entity whichmonitors a plurality of content items and detects which are new. Forthese new content items, a new virtual user preference profile may begenerated that provides a suitable association between the new contentitem and existing content items to be generated. A new content item maybe, for example, a content item that has not previously been rated, isnot included in a list of content items, is received from a specificsource or meets a set of predetermined criteria and/or characteristics.This provides a system wherein suitable content items are automaticallyassociated with existing content items to ensure an increasedprobability of recommendation.

According to another feature of the invention, the information of anavailability of the content item is received from a source which is notpart of the community-based recommendation system. The information maybe received, for example, by a dedicated information message provided byan external source. The information may thus be provided independentlyof the operation of the community-based recommendation system. Thisallows a content item to be introduced to the community-basedrecommendation system without any need for involving an operator orcentral controller of the community-based recommendation system.Additionally or alternatively, the external source may be an existingsource and could comprise, for example, news information sources, and inparticular news information sources specifically aimed at the typicalusers of the community-based recommendation system and/or related to oneor more categories of content items of the community-basedrecommendation system.

According to another feature of the invention, the at least one relatedcontent item is determined from a category to which the first contentitem belongs. Preferably, the category is determined from acorrespondence of at least one of the following: an artist; a contentitem type; and a music style. This ensures a suitable and reliableapproach to determining a related content item. For example, a givencontent item belonging to a specific category, such as a musical numberof a specific music style, and by a specific artist, may lead to allother musical numbers of that artist in that music style beingidentified and determined as related content. The preference value ofall of these content items may accordingly be set to have a suitablepreference value in the user preference profile, wherein an associationis formed to the first content item. This may lead to the first contentitem being recommended to users that have high preference values for oneor more of the other musical numbers of that artist and/or that musicstyle.

According to another feature of the invention, the method furthercomprises the step of setting the first preference value in response toa predetermined preference value profile. Preferably, the predeterminedpreference value is determined in response to a characteristic featureof the first content item. For example, a high preference value may beset for content items being associated with a first category and/orartist. This may cause all content items of that category and/or artistto be increasingly recommended. If the first content item is determinedto relate to a different category and/or artist, the rating may be, forexample, lower so that the probability of recommendation is reduced butis still present. It thus allows a further graduation of the probabilityof recommendation of content item and/or an automatic establishment of auser preference profile having the desired characteristics and impact onrecommendations.

According to another feature of the invention, the step of setting thefirst preference value comprises determining a category of the firstcontent item and setting the first preference value to the predeterminedpreference value profile for the category. This provides a suitableapproach to setting the first preference value to a desired value.

According to another feature of the invention, the method furthercomprises the steps of: initializing an element of a second userpreference profile with a preference value, the element being associatedwith the first content item; determining at least one related contentitem related to the first content item; and setting a further preferencevalue of an element of the second user preference profile associatedwith the at least one related content item.

Preferably, two or more user preference profiles are generated inresponse to receiving information of the availability of the firstcontent item. The two or more different user preference profiles mayspecifically have different preference values related to the firstcontent item and/or at least one related content item. Furthermore, thesecond user preference profile may set preference values of otherrelated content items than the ones set for the first user preferenceprofile. Two or more user preference profiles allow targeting ofseparate and various groups.

According to a second aspect of the invention, an apparatus foroperating with content items in a community-based recommendation systemcomprises: a receiver for receiving information of an availability of afirst content item; an initialization processor for initializing a firstelement of a user preference profile with a first preference value, thefirst element being associated with the first content item; a relationprocessor determining at least one related content item related to thefirst content item; and a profile processor for setting a secondpreference value of an element of the user preference profile associatedwith the at least one related content item.

These and other aspects of the invention are apparent from and will beelucidated with reference to the embodiment(s) described hereinafter.

An embodiment of the invention will be described, by way of exampleonly, with reference to the drawings, in which

FIG. 1 is an illustration of a community-based recommendation systemcomprising an apparatus for operating with content items in accordancewith an embodiment of the invention; and

FIG. 2 is an illustration of a method of operating with content items inaccordance with an embodiment of the invention.

The following description focuses on an embodiment of the invention in acentrally based community-based recommendation system. However, it willbe apparent that the invention is not limited to this application butmay be applied to many recommendation systems including non-centrallybased community-based recommendation systems. In the described example,individual user preference profiles are generated and maintained inindividual user terminals but it will be apparent that user preferenceprofiles may be generated in any suitable way and at any suitablephysical, architectural or logical location.

FIG. 1 is an illustration of a community-based recommendation systemcomprising an apparatus for operating with content items in accordancewith an embodiment of the invention.

The community-based recommendation system 100 has a centralrecommendation controller 101 and a plurality of user terminals 103 (twoshown). In the described embodiment, the central recommendationcontroller 101 may specifically be a website on the Internet providingmusic recommendations to a community. In this example, the centralrecommendation controller 101 only provides recommendations. In responseto a recommendation the user of a user terminal may access a suitablewebsite for downloading the recommended song. Specifically, the centralrecommendation controller 101 may include the IP address from which therecommended song may be downloaded. Typically, the IP address will bethat of a record label website from which the song can be downloaded fora given charge.

The central recommendation controller 101 comprises a recommendercommunication element 105 for receiving and transmitting data.Specifically, the recommender communication element 105 receives userpreference profiles from the user terminals 103 and transmitsrecommendations generated in response to the user terminals 103. Therecommender communication element 105 is connected to a recommender 107.The recommender is further connected to a user preference profiledatabase 109. The user preference profile database 109 comprisesinformation related to user preference profiles of the community. Hence,when a user preference profile is fed to the recommender 107, therecommender updates the user preference profile database 109 in responseto the received user preference profile. In a simple embodiment, eachuser preference profile is stored unaltered in the user preferenceprofile database 109. In more advanced embodiments, the information ofthe user preference profiles may be processed to generate more complexand suitable user preference information. For example, preferences of aplurality of users may be combined, averaged or grouped together toprovide additional and improved information.

When the recommender communication element 105 receives a userpreference profile from a user terminal 103, it is fed to therecommender. It is then added to the user preference profile database109 if it is not already comprised therein. If a version of the userpreference profile already exists in the user preference profiledatabase 109, this may be replaced or updated by the new user preferenceprofile. In addition, the recommender searches the user preferenceprofile database 109 to identify a user preference profile similar tothe one received. If one is identified, the content items of theequivalent user preference profile having a high preference value aregenerated as recommendations. The recommendations are fed to therecommender communication element 105 for transmission to the userterminals 103.

A user terminal 103 comprises a user terminal communication element 111for transmitting user preference profiles to and receivingrecommendations from the recommender 105. The user terminalcommunication element 111 is connected to a user interface 113 forpresentation to the user. The user interface 113 may specificallycomprise a display such as a computer monitor. In addition, the userterminals 103 in the described embodiment comprise a user preferenceprofile memory 114, wherein a user preference profile for the user isgenerated in response to the usage of the user terminal. The userpreference profile may thus typically comprise a list of various contentitems and a user rating of these. Thus, the user preference profilecomprises information of the user's preference for one or more contentitems.

The user preference profile may be communicated to the recommender 105at any suitable time. For example, the user preference profile may becommunicated at power up of the user terminal 103, when the userpreference profile is modified, when the user performs a special action,such as playing a content item, or when the user of the user terminal103 specifically requests a recommendation.

In addition to the user terminals, the community-based recommendationsystem 100 further comprises a virtual user terminal 115. The virtualuser terminal 115 comprises a receiver 117 for receiving information ofan availability of a first content item. Specifically, the receiver 117may receive information of the availability of the first content itemfrom an external source 119. In one embodiment, the external sourcespecifically provides information of content item availability to thevirtual user terminal 115, whereas in other embodiments, the virtualuser terminal 115 derives the information from analysis of informationretrieved from the external source. In the specific example, theexternal source may be an information source operated by a record labelto provide information of new songs being issued. Alternatively oradditionally, the external source may be a music Internet site accessedby the virtual user terminal 115 and scanned for information of newsongs that have been issued.

The virtual user terminal 115 further comprises a user preferenceprofile memory 121, wherein a user preference profile may be stored.Additionally, the virtual user terminal 115 comprises an initializationprocessor 123 for initializing a first element of a user preferenceprofile with a first preference value. The first element is associatedwith the first content item. The initialization processor 123 isconnected to the receiver 117 and the user preference profile memory121.

When the receiver 123 receives information of the availability of a newcontent item, it is fed to the initialization processor 123. Inresponse, the initialization processor 123 accesses the user preferenceprofile memory 121 to set a suitable preference value for the newcontent item. Specifically, the initialization processor 123 creates anentry for the new content item and assigns it a high preference value.

The virtual user terminal 115 further comprises a relation processor 125determining at least one related content item related to the firstcontent item. The relation processor 125 is connected to the receiver117 and when the availability of a new content item is identified, therelation processor 125 searches through the user preference profile toidentify related content items.

Hence, in the preferred embodiment, the user preference profilecomprises information of a plurality of content items. This informationmay be derived from previous content items identified through theexternal source, downloaded from the recommender 105, determined frommonitoring traffic of the community-based recommendation system or inany other suitable way. In other embodiments, a new user preferenceprofile may be generated for each new content item. In this case, one ormore related content items may be determined in any suitable way. Forexample, a user preference profile may be downloaded from therecommender or another user terminal, a database of content items (e.g.a music website) may be accessed to identify content item or contentitems may be received from the external source together with theinformation of the availability of a new content item.

In the preferred embodiment, content items are associated with one ormore different categories. For example, a content item category may be atype of the content item, such as, for example, a video clip or program,an audio clip or program, a text-based content item, a piece of softwareor a multimedia clip, etc. A category may further relate to the contentof the content items, such as, for example, an artist or music styleassociated with the content item. For example, a new content item whichis a song may be associated with a category of a song, of the artist, ofthe music style, of the length of the song, of a country of origin, etc.

In the preferred embodiment, a related content item is determined inresponse to the association of categories. Particularly, a relatedcontent item is determined from being in at least one category to whichthe first content item belongs. The category may specifically be acombined category such as the category of the specific artist and musicstyle. Hence, in the preferred embodiment, the relation processor scansthe user preference profile to identify all content items that have atleast one category in common with the new content item.

The virtual user terminal 115 further comprises a profile processor 127for setting a second preference value of an element of the userpreference profile associated with the at least one related contentitem. The profile processor 127 is connected to the relation processor125 and the user preference profile memory 121.

In the preferred embodiment, the profile processor 127 sets a preferencevalue in the user preference profile for all of the related contentitems identified by the relation processor 127. In a simple embodiment,the profile processor 127 simply sets a high preference values for allrelated content items. In this embodiment, when the availability of anew content item is detected, the preference values are set as high aspossible, not only for the new content item itself but also for othercontent items which are found to have a close correspondence with thenew content item. Hence, a strong association is established between thenew content item and existing similar content items. Consequently, theuse of this user preference profile in the central recommendationcontroller 101 is likely to cause the new content item to be recommendedto users having a high preference for the related content items. Hence,by not only setting a preference value for the new content item but alsofor related existing content items, the new content item is linked toexisting content items and thereby introduced to the community-basedrecommendation system.

In more advanced embodiments, the preference values of the relatedcontent items are similar to those of the first content item. Hence, ifthe first content item is given a high preference value, so are therelated content items. In other embodiments, the equivalence between thepreference values of the new content item and the related content itemsdepend on a degree of similarity between the content items.Specifically, the closer the correspondence between the new content itemand the related content items, the higher the correlation between theassigned preference values of the new content item and the relatedcontent items.

For example, in one embodiment, each content item may be associated witha plurality of categories. A related content item having the sameassociated categories as the new content item is set to have the samepreference value in the user preference profile as the new content item.Specifically, this may be a high preference value. A related contentitem having fewer categories in common with the new content item isgiven a lower preference value. Specifically, the preference valuedecreases for decreasing numbers of categories in common. A flexiblesetting of preference values for the related content item thus providesa further graduation in the association between the new content item andrelated content items.

The virtual user terminal 115 comprises a communication element 129connected to the user preference profile memory 121. The communicationelement 129 is operable to transmit the user preference profile of thevirtual user terminal 115 to the central recommendation controller 101.The communication element 129 may further be operable to receiveinformation related to the user preference profile database 109 for usein determining related content items.

Thus, in a preferred embodiment, the virtual user terminal 115 isoperable to generate a user preference profile for a community-basedrecommendation system. FIG. 2 is an illustration of a method ofoperating with content items in accordance with an embodiment of theinvention. The method is applicable to the virtual user terminal 115 ofFIG. 1.

In step 201, the receiver 117 receives information of an availability ofa first content item. In step 203, the initialization processor 123initializes a first element of a user preference profile with a firstpreference value, the first element being associated with the firstcontent item. In step 205, the relation processor determines at leastone related content item related to the first content item. In step 207the profile processor 127 sets a second preference value of an elementof the user preference profile associated with the at least one relatedcontent item. In step 209, the communication element 129 transmits theuser preference profile to the central recommendation controller 101.

In the preferred embodiment, the virtual user terminal 115 furtherdetermines if the first content item is a new content item. The steps ofinitializing, determining and setting the preference values in the userpreference profile are only performed if the first content item isdetermined to be new. Any suitable algorithm and criterion fordetermining a content item to be new may be used. Specifically, acontent item may be determined to be new if it has not already beenrated and specifically if it is not comprised in the user preferenceprofile database 109. In the preferred embodiment, a user preferenceprofile is thus only generated for new content items.

In the preferred embodiment, the preference value of the new contentitem is set in response to a predetermined preference value profile, andthe preference value is preferably further determined in response to acharacteristic of the first content item. In this embodiment, apredetermined preference value profile is generated comprisingpreference values set for a plurality of different categories of contentitems. For example, a first preference value may be assigned to contentitems associated with a first artist, a second preference value tocontent items associated with a second artist, and so on. When a newcontent item is identified, it is determined in which category the newcontent item belongs, and the associated preference value is assigned.This provides a graduation of the preference values assigned, and thusallows that the initial strength of the preference (and thus theprobability of recommendation) may be controlled in accordance with aspecific profile. As a specific example, a record label may have apredetermined preference value profile wherein all content items fromthat record label have a very high preference value, and all contentitems from other record labels have a low or neutral preference value.This will allow the record label to automatically bias recommendationstowards new content items from the record label.

The preferred embodiment thus ensures that by not only setting apreference value of the new content item but also of related contentitem(s), an association is created to other content items, and thus thenew content item is linked to the existing recommendation system.Furthermore, as the related content items and/or preference values canbe selected to have a desired effect on the recommendations, the newcontent item can be aimed at a suitable target group. Specifically, anew content item need not be recommended in general to a large group ofusers but can be specifically recommended to a small group of usershaving a high preference for similar content items. This ensures atargeted introduction of new content in a community-based recommendationsystem.

It will be apparent that the user preference profile need not begenerated in the individual user terminals. For example, in otherembodiments, all user preference profiles are generated and stored in acentral recommendation unit. The user preference profile of a user mayin this example be generated from the behavior of a user such as, forexample, the selections of content items made by a user. It will furtherbe apparent that the recommendation function need not be implementedcentrally but may be, for example, performed in individual userterminals in response to received user preference profile informationrelating to other users.

Although the above description has focused on generating of one specificuser preference profile, a plurality of different user preferenceprofiles may be generated in response to detecting that a new contentitem is available. Effectively, the process described above may beiterated for different user preference profiles using modified criteria.

As a specific example, a new content item may be a poem converted into apopular song. In this case, a first user preference profile may begenerated, which aimes at a group of users interested in popular songsand music but perhaps not poetry. A second user preference profile maybe generated for a group of users having a high preference for poetrybut a low preference value for popular music. In this way, the newcontent item is linked to both user groups. Hence, generation ofmultiple user preference profiles allows targeting of a plurality ofvarious groups, which may overlap only in the specific area of the newcontent item.

The invention can be implemented in any suitable form includinghardware, software, firmware or any combination of these. However, theinvention is preferably implemented as computer software running on oneor more data processors and/or digital signal processors. The elementsand components of an embodiment of the invention may be physically,functionally and logically implemented in any suitable way. Indeed, thefunctionality may be implemented in a single unit, in a plurality ofunits or as part of other functional units. As such, the invention maybe implemented in a single unit or may be physically and functionallydistributed between different units and processors.

Although the present invention has been described in connection with thepreferred embodiment, it is not intended to be limited to the specificform set forth herein. Rather, the scope of the present invention islimited only by the accompanying claims. In the claims, use of the verb“comprise” and its conjugations does not exclude the presence of otherelements or steps. Furthermore, although individually stated, aplurality of means, elements or method steps may be implemented by e.g.a single unit or processor. Moreover, although individual features maybe included in different claims, these may possibly be advantageouslycombined, and the inclusion in different claims does not imply that acombination of features is not feasible and/or advantageous. Inaddition, singular references do not exclude a plurality. Thusreferences to “a”, “an”, “first”, “second” etc do not preclude aplurality.

1. A method of operating with content items in a community-basedrecommendation system; the method comprising the steps of: initializing(203) a first element of a user preference profile with a firstpreference value, the first element being associated with a firstcontent item; determining (205) at least one related content itemrelated to the first content item; and setting (207) a second preferencevalue of an element of the user preference profile, associated with theat least one related content item.
 2. A method as claimed in claim 1,further comprising a step of receiving information (201) of anavailability of the first content item.
 3. A method as claimed in claim1, wherein the second preference value is similar to the firstpreference value.
 4. A method as claimed in claim 1, wherein the firstpreference value is a high preference value.
 5. A method as claimed inclaim 1, wherein an equivalence of the first preference value and thesecond preference value is determined in response to a degree ofsimilarity between the first content item and the at least one relatedcontent item.
 6. A method as claimed in claim 1, further including thesteps of determining if the first content item is a new content item andwherein the steps of initializing, determining and setting are onlyperformed if the first content item is new.
 7. A method as claimed inclaim 2 wherein the information of an availability of the content itemis received from a source which is not part of the community-basedrecommendation system.
 8. A method as claimed in claim 1, wherein the atleast one related content item is determined from a category to whichthe first content item belongs.
 9. A method as claimed in claim 8,wherein the category is determined from a correspondence of at least oneof the following: a. an artist; b. a content item type; and c. a musicstyle.
 10. A method as claimed in claim 1, further comprising the stepof setting the first preference value in response to a predeterminedpreference value profile.
 11. A method as claimed in claim 10, whereinthe first preference value determined in response to the predeterminedpreference value profile is determined in response to a characteristicof the first content item.
 12. A method as claimed in claim 10, whereinthe step of initializing (203) a first element of the user preferenceprofile with the first preference value comprises determining a categoryof the first content item and setting the first preference value to thepredetermined preference value profile for the category.
 13. A method asclaimed in claim 1, further comprising the steps of: initializing anelement of a second user preference profile with a preference value, theelement being associated with the first content item; determining atleast one related content item related to the first content item; andsetting a further preference value of an element of the second userpreference profile associated with the at least one related contentitem.
 14. A computer program enabling a method to be carried outaccording to claim
 1. 15. A record carrier comprising a computer programas claimed in claim
 14. 16. An apparatus for operating with contentitems in a community-based recommendation system; the apparatuscomprising: a receiver (117) for receiving information of anavailability of a first content item; an initialization processor (123)for initializing a first element of a user preference profile with afirst preference value, the first element being associated with thefirst content item; a relation processor (125) determining at least onerelated content item related to the first content item; and a profileprocessor (127) for setting a second preference value of an element ofthe user preference profile associated with the at least one relatedcontent item.
 17. A community-based recommendation system comprising anapparatus as claimed in claim 16.